bivariate.mixalg: EM algorithm and classification for univariate data, for...

Description Usage Arguments Examples

View source: R/CAMAN.R

Description

Function

Usage

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bivariate.mixalg(obs1, obs2, type, data = NULL, 
                 var1, var2, corr, lambda1, lambda2,
                 p,startk, numiter=5000, acc=1.e-7, class)

Arguments

obs1

the first column of the observations


obs2

the second column of the observations


type

kind of data


data

an optional data frame


var1

Variance of the first column of the observations(except meta-analysis)


var2

Variance of the second column of the observations (except meta-analysis)


corr

correlation coefficient


lambda1

Means of the first column of the observations


lambda2

Means of the second column of the observations


p

Probability


startk

starting/maximal number of components. This number will be used to compute the grid in the VEM. Default is 20.


numiter

parameter to control the maximal number of iterations in the VEM and EM loops. Default is 5000.


acc

convergence criterion. Default is 1.e-7


class

classification of studies


Examples

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## Not run: 
#1.EM and classification for bivariate data
#Examples
data(rs12363681)
test <- bivariate.mixalg(obs1=x, obs2=y, type="bi", 
                         lambda1=0, lambda2=0, p=0, 
                         data=rs12363681, startk=20, class="TRUE")
#scatter plot with ellipse
plot(test)
#scatter plot without ellipse
plot(test, ellipse = FALSE)
#2.EM and classification for meta data
#Examples
data(CT)
bivariate.mixalg(obs1=logitTPR, obs2=logitTNR, 
                 var1=varlogitTPR, var2=varlogitTNR,
                 type="meta", lambda1=0, lambda2=0,
                 p=0,data=CT,startk=20,class="TRUE")

## End(Not run)

CAMAN documentation built on May 1, 2019, 9:21 p.m.